EECS Prof. Emeritus Kam Lau, has won the 2022 California Institute of Technology Distinguished Alumni Award, the highest honor presented by Caltech to its alumni.  He was cited "for extraordinary contributions to society as an engineer, entrepreneur, and artist." Lau is known for his pioneering developments and commercialization of RF over fiber devices, systems and applications, which helped launch the microwave photonics industry.  He received his B.S., M.S., and Ph.D degrees from Caltech in 1978, 1978 and 1981, respectively.  Before coming to Berkeley in 1990, he was founding chief scientist of Ortel Corporation, and a professor at Columbia University.  He subsequently  co-founded LGC Wireless with some of his Berkeley colleagues.  Lau is also an accomplished ink painting artist.  At age 16, his work was accepted into the 1972 Hong Kong Contemporary Art Exhibition, a venue for professional artists, and one of his pieces was acquired by the Hong Kong Museum of Art for its permanent collection.

Databricks, a cloud startup founded by CS Adjunct Assistant Prof. Ali Ghodsi, CS Prof. Scott Shenker, CS Prof. Ion Stoica, and alumni Andrew Konwinski (M.S. '09/Ph.D. 12, advisor: Randy Katz), Reynold Xin (Ph.D. '13, advisor: Ion Stoica), Patrick Wendell (M.S. '13, advisor: Ion Stoica), and Matei Zaharia (Ph.D. '13, advisors: Scott Shenker & Ion Stoica), has received $1 billion in a Series G funding round.  Franklin Templeton led the round and now values the company at $28 billion.  Amazon Web Services, CapitalG, the growth equity arm of Google parent Alphabet, and Salesforce Ventures are backing Databricks for the first time, while Microsoft joins a group of existing investors including BlackRock, Coatue, T. Rowe Price and Tiger Global.  Ghodsi, who is CEO of the company, says Databricks plans to use the funds to accelerate its international presence. “This lets us really hit the gas and go aggressive in these big markets. It’s almost like starting the company all over again,” he says.  Databricks grew out of the AMPLab project and is built on top of Apache Spark, an open-source analytics tool developed at Berkeley.  The company provides data analytics and AI tools to businesses.  It has grown more than 75% year-over-year, with the majority of its revenue coming from enterprises like Comcast, Credit Suisse, Starbucks and T-Mobile, who use it as a "data lake house"--a place to store structured and unstructured data, then layer business intelligence or machine-learning tools easily on top.

Ambidextrous, a company co-founded in 2018 by CS Prof. Ken Goldberg, his graduate student Jeffrey Mahler (CS Ph.D. '18), and AutoLab postdocs (and ME alumni) Stephen McKinley (M.S. '14/Ph.D. '16) and David Gealy (B.S. '15), has won the inaugural Silicon Valley Robotics (SVR) ‘Good Robot’ Innovation and Overall Excellence Industry Award.  Ambidextrous utilizes an AI-enhanced operating system, Dexterity Network (Dex-Net) 4.0, that empowers versatile robots for automated e-commerce order fulfillment by allowing them to learn to pick, scan, and pack a wide variety of items in just a few hours.  This universal picking (UP) technology has enabled new levels of robotic flexibility, reliability, and accuracy.

CS Prof. Ken Goldberg is the co-author of a study published in Science Robotics which describes the creation of a new artificial intelligence software that gives robots the speed and skill to grasp and smoothly move objects, making it feasible for them to soon assist humans in warehouse environments.  He and postdoc Jeffrey Ichnowski had previously created a Grasp-Optimized Motion Planner that could compute both how a robot should pick up an object and how it should move to transfer the object from one location to another, but the motions it generated were jerky.  Then they, along with EECS graduate student Yahav Avigal and undergraduate (3rd year MS) student Vishal Satish, integrated a deep learning neural network into the motion planner, cutting the average computation time from 29 seconds to 80 milliseconds, or less than one-tenth of a second.  Goldberg predicts that, with this and other advances in robotic technology, robots could be assisting in warehouse environments in the next few years.

EECS alumnus and Prof. Ali Niknejad (M.S. '97/Ph.D. '00, advisor: Robert Meyer) has won the 2020 Semiconductor Industry Association (SIA) University Research Award.  This award recognizes researchers in both technology and design who have made “a lifetime of great impact to the semiconductor industry.”  Niknejad was cited for “noteworthy achievements that have advanced analog, RF, and mm-wave circuit design and modeling, which serve as the foundation of 5G+ technologies.”  Stanford ME Prof. Kenneth Goodson also won the award this year.  “Research is the engine of innovation in the semiconductor industry, enabling breakthroughs that power our economy and help solve society’s great challenges,” said John Neuffer, SIA president and CEO. “The work of Drs. Goodson and Niknejad has greatly advanced chip technology and helped keep America at the leading edge of innovation.”  Niknejad, who previously received the 2012 ASEE Frederick Emmons Terman Award for his textbook on electromagnetics and RF integrated circuits, will accept the SIA award during the 2020 SIA Leadership Forum and Award Celebration on November 19th.

EECS Prof. Emeritus Michael Stonebraker has won the prestigious NEC Computers and Communications (C&C) Prize "For Pioneering Contributions to Relational Database Systems." The prize is awarded "to distinguished persons in recognition of outstanding contributions to research and development and/or pioneering work in the fields of semiconductors, computers, and/or telecommunications and in their integrated technologies."  In the early 1970's, Stonebraker and Prof. Eugene Wong began researching Relational Database Management Systems (RDBMS), which culminated in the creation of the Interactive Graphics and Retrieval System (INGRES), a practical and efficient implementation of the relational model running on Unix-based DEC machines.  It included a number of key ideas still widely used today, including B-trees, primary-copy replication, the query rewrite approach to views and integrity constraints, and the idea of rules/triggers for integrity checking in an RDBMS.  Stonebraker, Wong, and Prof. Larry Rowe, founded a startup called Relational Technology, Inc. (renamed Ingres Corporation), which they sold to Computer Associates in the early 1990's for $311M.  Stonebraker's student, Robert Epstein (Ph.D. '80), founded the startup Sybase, which created the code used as a basis for the Microsoft SQL Server.  Stonebraker also created Postgres in the late 1980's, which made it easier for programmers to modify or add to the optimizer, query language, runtime, and indexing frameworks.  It broadened the commercial database market by improving both database programmability and performance, making it possible to push large portions of a number of applications inside the database, including geographic information systems and time series processing.  Stonebraker retired from Berkeley in 2000 to found more companies and become an adjunct professor at MIT.  His achievements have been recognized with an IEEE John von Neumann Medal in 2005, ACM A.M. Turing Award in 2014, and ACM SIGMOD Systems Award in 2015.

EE alumnus Colin Parris (M.S. '87, Ph.D. '94, advisor: Domenico Ferrari), the Ken Kennedy keynote speaker at the 2020 ACM Richard Tapia Celebration of Diversity in Computing Conference, is the subject of a CMDIT interview.  He talks about his childhood, the value of diversity in technological fields, and what young people interested in tech careers should know.  His keynote lecture, titled "How Digital Technology Will Shape the Future of Business," discussed how AI's physical/digital marriage can accelerate business growth and create new opportunities for people who want to find solutions to some of the world's biggest problems.  Parris is currently the Senior Vice President and Chief Technology Officer at GE Digital.

EECS Prof. Ana Claudia Arias has been selected to participate in a new food systems research institute funded by the National Science Foundation (NSF),  US Department of Agriculture (USDA), and the National Institute of Food and Agriculture (NIFA).  The award of $20M over five years will aim to improve US food systems to address issues such as pandemic-driven food system security and safety; improving crop yield, quality and nutrition; decreasing energy and water resource consumption; and increasing production and eliminating food waste.  The objective of the new USDA-NIFA Institute for Artificial Intelligence for Next-Generation Food Systems (AIFS) will focus on the creation of digital replicas of complex food systems, so-called “digital twins,” which can be safely manipulated and optimized in a virtual world and deployed in the physical world afterwards, reducing costs of experiments and accelerating development of new technologies.  A team of ten researchers from the UC Berkeley Next Generation Food Systems Center will combine forces with researchers from five other institutions including UC Davis, Cornell, UIUC, UC ANR, and the USDA, to staff the new center.